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الصفحة 3
الصفحة 3
Assessment and future directions of nonlinear model predictive control
Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.
Arctic-Subarctic Ocean Fluxes : Defining the Role of the Northern Seas in Climate
The two-way oceanic exchanges that connect the Arctic and Atlantic oceans through subarctic seas are of fundamental importance to climate. Change may certainly be imposed on the Arctic Ocean from subarctic seas, including a changing poleward ocean heat flux that is central to determining the present state and future fate of the perennial sea-ice. And the signal of Arctic change is expected to have its major climatic impact by reaching south through subarctic seas, either side of Greenland, to modulate the Atlantic thermohaline ‘conveyor’. Developing the predictive skills of climate models is seen to be the most direct way of extending the ability of society to mitigate for or adapt to 'global change' and is the main justification for continuing an intense observational effort in these waters. As records have lengthened, they have shown that important aspects of oceanic exchange through subarctic seas are currently at a long-term extreme state, providing further motivation for their study.
Agriculture and Climate Beyond 2015 : A New Perspective on Future Land Use Patterns
Interactions between agriculture, climate and patterns of land use are complex. Major changes in agriculture, and land use patterns are foreseen in the next couple of decades in response to shifts in climate, greenhouse gas management initiatives, population growth and other forces. The book explores key interactions between changes in agriculture, patterns of land use and efforts to reduce greenhouse emissions from agriculture. The volume is based on inter-disciplinary science and policy interactions, exploring the way land use may aid in addressing or be affected by the onset of climate change and alterations in food demand. Future forces shaping land use decisions are examined, and its sensitivity to climate change is highlighted. Patterns of land use and the agricultural role in climate change mitigation are explored. Also, policy and social responses to the new perspectives on future land use patterns are identified. The perspective of the book is beyond the year 2015.
A Theory of Shape Identification
Recent years have seen dramatic progress in shape recognition algorithms applied to ever-growing image databases. They have been applied to image stitching, stereo vision, image mosaics, solid object recognition and video or web image retrieval. More fundamentally, the ability of humans and animals to detect and recognize shapes is one of the enigmas of perception. The book describes a complete method that starts from a query image and an image database and yields a list of the images in the database containing shapes present in the query image. A false alarm number is associated to each detection. Many experiments will show that familiar simple shapes or images can reliably be identified with false alarm numbers ranging from 10-5 to less than 10-300.
